Exemple #1
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def test_zeros():
    zeros = np.zeros((64,64), np.uint8)
    feats = texture.haralick(zeros)
    assert not np.any(np.isnan(feats))

    feats = texture.haralick(zeros, ignore_zeros=True)
    assert not np.any(np.isnan(feats))
Exemple #2
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def test_zeros():
    zeros = np.zeros((64,64), np.uint8)
    feats = texture.haralick(zeros)
    assert not np.any(np.isnan(feats))

    feats = texture.haralick(zeros, ignore_zeros=True)
    assert not np.any(np.isnan(feats))
def test_haralick3d():
    np.random.seed(22)
    img = mahotas.stretch(255 * np.random.rand(20, 20, 4))
    features = texture.haralick(img)
    assert features.shape == (13, 13)

    features = texture.haralick(img[:, :, 0])
    assert features.shape == (4, 13)
Exemple #4
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def test_haralick3d():
    np.random.seed(22)
    img = mahotas.stretch(255*np.random.rand(20,20,4))
    features = texture.haralick(img)
    assert features.shape == (13,13)

    features = texture.haralick(img[:,:,0])
    assert features.shape == (4,13)
Exemple #5
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def test_haralick3d():
    np.random.seed(22)
    img = mahotas.stretch(255*np.random.rand(20,20,4))
    features = texture.haralick(img)
    assert features.shape == (13,13)

    features = texture.haralick(img[:,:,0])
    assert features.shape == (4,13)

    features = texture.haralick(img.max(0), ignore_zeros=True, preserve_haralick_bug=True, compute_14th_feature=True)
    assert features.shape == (4,14)
Exemple #6
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def test_haralick3d():
    np.random.seed(22)
    img = mahotas.stretch(255*np.random.rand(20,20,4))
    features = texture.haralick(img)
    assert features.shape == (13,13)

    features = texture.haralick(img[:,:,0])
    assert features.shape == (4,13)

    features = texture.haralick(img.max(0), ignore_zeros=True, preserve_haralick_bug=True, compute_14th_feature=True)
    assert features.shape == (4,14)
def compute_fluor_info(seg, fluor_img):
    rps = regionprops(seg)

    mean_intensity = np.zeros((len(rps)))
    std_intensity = np.zeros((len(rps)))
    intensity_range = np.zeros((len(rps)))
    fluor_haralick = []
    for i in range(len(rps)):
        cell_num = int(i + 1)
        r = rps[i]
        cell_mask = (seg == cell_num)
        region_cell_mask = cell_mask[r.bbox[0]:r.bbox[2], r.bbox[1]:r.bbox[3]]

        crop_img = fluor_img[r.bbox[0]:r.bbox[2], r.bbox[1]:r.bbox[3]]
        cell_img = (fluor_img * cell_mask)[r.bbox[0]:r.bbox[2],
                                           r.bbox[1]:r.bbox[3]]

        mean_intensity[i] = np.sum(cell_img) * 1.0 / r.area
        std_intensity[i] = np.std(cell_img[region_cell_mask])

        min_value, max_value = np.amin(cell_img[region_cell_mask]), np.amax(
            cell_img[region_cell_mask])
        min_value = min_value - 1

        intensity_range[i] = max_value - min_value

        #the haralick features have four directions, to meet rotation invariance,use average for each feature
        fl_hara = np.mean(mht.haralick(cell_img, ignore_zeros=True), axis=0)

        fluor_haralick.append(fl_hara)
    fluor_haralick = np.array(fluor_haralick)

    return mean_intensity, std_intensity, intensity_range, fluor_haralick
 def _calculateStatistics(self, img, haralick=False, zernike=False):
     result = []
     # 3-bin histogram
     result.extend(mquantiles(img))
     # First four moments
     result.extend([img.mean(), img.var(), skew(img, axis=None), kurtosis(img, axis=None)])
     # Haralick features
     if haralick:
         integerImage = dtype.img_as_ubyte(img)
         result.extend(texture.haralick(integerImage).flatten())
     # Zernike moments
     if zernike:
         result.extend(zernike_moments(img, int(self.rows) / 2 + 1))
     return result
Exemple #9
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 def _calculateStatistics(self, img, haralick=False, zernike=False):
     result = []
     #3-bin histogram
     result.extend(mquantiles(img))
     #First four moments
     result.extend([
         img.mean(),
         img.var(),
         skew(img, axis=None),
         kurtosis(img, axis=None)
     ])
     #Haralick features
     if haralick:
         integerImage = dtype.img_as_ubyte(img)
         result.extend(texture.haralick(integerImage).flatten())
     #Zernike moments
     if zernike:
         result.extend(zernike_moments(img, int(self.rows) / 2 + 1))
     return result
def _compute_haralick_features(patch, distance):
    """Compute the haralick feature.

    This function is used for parallel processing.

    Parameters
    ----------
    patch: ndarray, (patch_size)
        The patch to consider to compute the cooccurence matrix.

    distance: int,
        The distance to use to compute the cooccurence matrix.

    Returns
    -------
    haralick_features: ndarray, shape (4, 13)
        The haralick features.
    """

    return haralick(patch, distance=distance)
Exemple #11
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    def img_feature_extraction(self, img):
        # Change CHW to HWC
        HWC_img = img_as_float(img.permute(1, 2, 0))
        segments_slic = slic(HWC_img, n_segments=20, compactness=10, sigma=1, start_label=1)
        unique_lables = np.unique(segments_slic)
        if 0 in unique_lables:
            unique_lables = np.delete(unique_lables, 0)
        N = len(unique_lables)
        image = np.zeros((N, 19))
        # image = np.zeros((N, 6))
        regions = measure.regionprops(segments_slic, intensity_image=HWC_img)
        for (i, segVal) in enumerate(unique_lables):
            # convert image to grayscale
            ubyte_img = img_as_ubyte(HWC_img)
            ubyte_img[ubyte_img == 0] = 1
            gray = cv2.cvtColor(ubyte_img, cv2.COLOR_BGR2GRAY)

            # construct a mask for the segment
            mask = np.zeros(gray.shape, dtype=np.bool)
            mask[segments_slic != segVal] = True
            gray[mask] = 0

            # extract texture feature from mahotas package
            texture_features = texture.haralick(gray, ignore_zeros=True)
            ht_mean = texture_features.mean(axis=0)

            # extract mean_intensity feature
            mean_intensity = regions[i].mean_intensity

            # extract centroid feature
            centroid = regions[i].centroid

            #extract area feature
            area = regions[i].area

            image[i] = np.hstack((mean_intensity,centroid, area, ht_mean))
            # image[i] = np.hstack((mean_intensity, centroid, area))
        return image
Exemple #12
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def test_4d_image():
    texture.haralick(np.arange(4**5).reshape((4,4,4,4,4)))
Exemple #13
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def test_ignore_zeros_raise():
    zeros = np.zeros((64,64), np.uint8)
    texture.haralick(zeros, ignore_zeros=True)
regions = measure.regionprops(segments_slic, intensity_image=img)
print(len(regions))
if 0 in c:
    c = np.delete(c, 0)
for (i, segVal) in enumerate(c):
    # construct a mask for the segment
    print(i)
    new = img_as_ubyte(img)
    new[new == 0] = 1
    gray = cv2.cvtColor(new, cv2.COLOR_BGR2GRAY)
    # print(i)
    # print(new)
    mask = np.zeros(gray.shape, dtype=np.bool)
    mask[segments_slic != segVal] = True
    gray[mask] = 0
    features = texture.haralick(gray, ignore_zeros=True)
    ht_mean = features.mean(axis=0)
    a = np.hstack((regions[i].mean_intensity, regions[i].centroid, ht_mean))
    print(regions[i].mean_intensity)
    # print(regions[i].centroid)
    # print(ht_mean)
    # print(a.shape)

fig, ax = plt.subplots(2, 2, figsize=(10, 10), sharex=True, sharey=True)

ax[0, 1].imshow(mark_boundaries(img, segments_slic))
ax[0, 1].set_title('SLIC')

for a in ax.ravel():
    a.set_axis_off()
Exemple #15
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def test_float_haralick():
    A = np.zeros((5,5), np.float32)
    A[2,2]=12
    texture.haralick(A)
Exemple #16
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def test_haralick3():
    np.random.seed(123)
    f = np.random.rand(34, 12, 8)
    f = (f * 255).astype(np.int32)
    feats = texture.haralick(f)
    assert not np.any(np.isnan(feats))
Exemple #17
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def test_ignore_zeros_raise():
    zeros = np.zeros((64, 64), np.uint8)
    texture.haralick(zeros, ignore_zeros=True)
def test_4d_image():
    with pytest.raises(ValueError):
        texture.haralick(np.arange(4**5).reshape((4, 4, 4, 4, 4)))
def test_ignore_zeros_raise():
    zeros = np.zeros((64, 64), np.uint8)
    with pytest.raises(ValueError):
        texture.haralick(zeros, ignore_zeros=True)
def test_float_haralick():
    A = np.zeros((5, 5), np.float32)
    A[2, 2] = 12
    with pytest.raises(TypeError):
        texture.haralick(A)
def test_haralick3():
    np.random.seed(123)
    f = np.random.rand(34, 12, 8)
    f = (f * 255).astype(np.int32)
    feats = texture.haralick(f)
    assert not np.any(np.isnan(feats))
Exemple #22
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def test_4d_image():
    texture.haralick(np.arange(4**5).reshape((4,4,4,4,4)))
Exemple #23
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def test_float_haralick():
    A = np.zeros((5,5), np.float32)
    A[2,2]=12
    texture.haralick(A)